Company: DWT Business Type: Startup Company Type: Product & Service Business Model: B2B Funding Stage: Bootstrapped Industry: PHARMA

Job Description
Position Overview
• Openings: 2 Positions
• Industry Context: Pharmaceutical and Life Sciences Role Summary We are seeking 2 Lead AI Engineers with deep expertise in agentic systems architecture and production LLM deployments. In this role, you will design and ship multi-agent pipelines, advanced RAG architectures, and tool-orchestration layers tailored for life sciences, pharma commercial analytics, and medical affairs workflows. You will serve as a technical pod lead—guiding junior engineers, conducting design reviews, and ensuring enterprise-grade compliance (HIPAA, GxP, 21 CFR Part 11).

Key Responsibilities
• Agentic Architecture: Design and implement multi-agent graphs, tool orchestration layers, memory systems, and retrieval modules using LangGraph, AutoGen, CrewAI, or MCP.
• Production RAG Pipelines: Build and optimize high-performance RAG workflows (document ingestion, chunking, hybrid search, embedding selection, and latency tuning).
• Life Sciences Integration: Integrate agentic systems with pharma platforms (IQVIA, Symphony, Komodo, Veeva Vault, Medidata) via REST, event-driven hooks, and batch patterns.
• Observability & Ops: Own component-level telemetry, trace logging, cost tracking, and drift alerts using LangSmith or Helicone.
• Technical Leadership: Lead subsystem designs (agent topology, API contracts,



failure handling), conduct code reviews, and act as the day-to-day technical mentor on the pod.
• Compliance & Quality: Apply GxP traceability, HIPAA-compliant handling, and 21 CFR Part 11 auditability patterns across all modules. Mandatory Requirements & Tech Stack
•

Experience:
6+ years of software/ML engineering, with 2+ years building and shipping production LLM or agentic AI systems (at least 2 systems taken live to production with benchmarks).
• Programming & Cloud: Master-level Python (type annotations, testing, profiling); Cloud deployment on AWS, Azure, or GCP using Docker, Kubernetes, Terraform/CDK, and CI/CD.
• Frameworks & SDKs: Hands-on proficiency with agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI) and direct SDK usage of Anthropic Claude API, OpenAI Assistants API, or Vertex AI Agent Builder.
• Vector Stores & RAG: Expertise with vector databases (Pinecone, Weaviate, pgvector), hybrid search, and evaluation frameworks (RAGAS).
• Domain Context: Exposure to regulated data environments (HIPAA, GxP, 21 CFR Part 11) and pharma commercial data (Rx/claims, medical affairs, or clinical ops).

What We Offer
• Competitive compensation package (CTC inclusive of 10% variable).
• Hybrid flexibility with structured WFH allowances.
• Prospect to work at the bleeding edge of agentic AI and Model Context Protocol (MCP) in the life sciences sector.

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